Examkin

Question

Difficulty: MediumPlanning Compute Engine Resources and Machine Types

An e-commerce enterprise is planning its Google Cloud Compute Engine resource strategy for two distinct backend services:

1. An image processing service that runs batch resizing jobs on user-uploaded media. The jobs are stateless, fault-tolerant, and support checkpointing.
2. A 24/7 high-performance in-memory inventory caching service that requires massive RAM capacity and uninterrupted availability.

Which TWO deployment strategies should the cloud engineer implement to optimize cost and performance for these workloads? (Select TWO.)

  1. Deploy Spot VM instances for the image processing batch service to achieve significant cost savings for fault-tolerant tasks.Answer
  2. Deploy Memory-optimized (M-series) VM instances backed by Committed Use Discounts (CUDs) for the inventory caching service.Answer
  3. C
    Deploy Spot VM instances for the inventory caching service to minimize hourly runtime costs for memory-heavy instances.
  4. D
    Apply automatic Sustained Use Discounts (SUDs) on top of Spot VM pricing for the image processing service to compound cost savings.

Answer

The correct strategies are deploying Spot VM instances for the stateless image processing batch service and deploying Memory-optimized (M-series) instances with Committed Use Discounts (CUDs) for the 24/7 in-memory inventory caching service.
The correct choices match workload characteristics to GCP compute offerings: Spot VMs deliver maximum cost efficiency for fault-tolerant, checkpointed batch jobs, while Memory-optimized instances combined with Committed Use Discounts (CUDs) ensure high RAM allocation and predictable pricing for continuous 24/7 workloads.

Step-by-Step Solution

1
Analyze the workload requirements for the image processing service.
The image processing workload is stateless, batch-oriented, fault-tolerant, and supports checkpointing.
Fault-tolerant batch jobs that can handle interruptions are prime candidates for Spot VMs, which provide significant savings over on-demand pricing.
2
Analyze the workload requirements for the inventory caching service.
The inventory caching workload requires high RAM capacity, continuous 24/7 operation, and zero unplanned downtime.
Memory-optimized (M-series) machine types suit memory-heavy databases and caches, while Committed Use Discounts (CUDs) provide 1-year or 3-year cost reductions for predictable, continuous usage.
3
Evaluate potential discounting mechanisms and anti-patterns.
Spot VMs cannot be combined with Sustained Use Discounts, and Spot VMs should never be used for non-fault-tolerant production caching layers.
Selecting appropriate machine families and provisioning models requires matching business SLA and uptime needs with GCP billing structures.

Key Concept

Compute Engine Machine Type Selection and Pricing Model Optimization
Estimated Time:2m 0s
Rate this question

Topics

Planning Compute Engine Resources and Machine Types

More questions from this topic